Design and Performance Evaluation of a Laboratory-made 200 nm Precut Electrical Cascade Impactor

Abstract

Increasing public concern regarding air quality has led to the development of efficient aerosol-monitoring techniques. Among the various aerosol measurement instruments based on electrical methods, in this study, an electrical cascade impactor (ECI) was designed and fabricated in our laboratory and was used to measure the real-time size distribution of submicron-sized aerosols. In the study by Park et al. (2007), it was assumed that the size distribution of incoming particles follows a unimodal lognormal distribution. However, in this study, the distribution of particles captured at each stage (including the Faraday cage) was assumed to be a unimodal lognormal distribution; hence, the incoming particles may follow any size distribution. After the particle charging characteristics were obtained for different particle sizes, experiments were performed with monodisperse test particles to determine the collection efficiency of each stage. The current measured in each stage was converted into a number based size distribution of aerosols by using the data inversion algorithm, which utilized the experimentally obtained collection efficiency. Then, a performance evaluation was performed, both in the laboratory and in the field. The results obtained by our ECI were in agreement with the scanning mobility particle sizer (SMPS) data.

Full text

Aerosol and Air Quality Research, 18: 849–855, 2018
Copyright © Taiwan Association for Aerosol Research
ISSN: 1680-8584 print / 2071-1409 online
doi: 10.4209/aaqr.2017.10.0408
A Comparison of PAH Emission Sampling Methods (Cyclone, Impactor) in
Particulate and Gaseous Phase
Jiří Horák
1
, Lenka Kuboňová
1*
, Kamil Krpec
1
, František Hopan
1
, Petr Kubesa
1
,
Jan Koloničný
1
, Daniela Plachá
2,3
1 Energy Research Center, VŠB-Technical University of Ostrava, 708 33 Ostrava-Poruba, Czech Republic
2 Nanotechnology Centre, VŠB-Technical University of Ostrava, 708 33 Ostrava-Poruba, Czech Republic
3 Centre Energy Units for Utilization of Non Traditional Energy Sources, VŠB-Technical University of Ostrava, 708 33
Ostrava-Poruba, Czech Republic
ABSTRACT
Four different domestic heating boilers and four types of fuel (lignite, wet wood, wood pellets and mixed fuel) were
tested, and the emissions of the particulate matter (PM) and polycyclic aromatic hydrocarbons (PAHs) were correlated.
Dekati low-pressure impactor (DLPI, Dekati) sorting of the PM fractions into PM0.1, PM1, PM2.5 and PM10 was used to
determine the emission factors of the PAHs in a dilution tunnel via isokinetic sampling and was compared with a cyclone
(Tecora). The 4 PAHs were mostly detected on the fine particles of PM1 in the DLPI and on the fine particles of PM2.5 in
the cyclone, and in some cases, they were mainly detected in polyurethane foam (PUF) used for the collection of the gas
phase placed behind the DLPI and cyclone. The effectiveness of DLPI sampling was generally comparable or lower than
the cyclone sampling of the range 0.01–1.33 mg kg–1.
Keywords: Domestic heating; Particulate matter; PAH sampling; Impactor DLPI; Cyclone.
INTRODUCTION
Residential stationary sources, including fireplaces,
stoves, cookers, masonry heaters and small boilers with
nominal outputs below 50 kW are one of the major sources
of emissions; in particular, they accounted for 68.3% of the
benzo[a]pyrene and 51.8% of the total PAH emissions (the
sum of 4 PAHs according to EMEP/EEA Guidebook
(Kubica, 2007; EEA, 2016)). The PAH concentrations are
the highest during winter, most probably due to residential
heating as a major PAH source (Cazier et al., 2016).
Polycyclic aromatic hydrocarbons (PAHs) comprise a
few hundred organic compounds consisting of 2 or more
condensed benzene rings. In general, high molecular weight
PAHs (4–6 rings) tend to be more concentrated in particle
phase, while the ones with lower molecular weight (2–3
rings) are often concentrated in gas phase (Li et al., 2016).
PAHs are formed during the incomplete combustion of
organic materials at high temperature. UNECE nomenclature
for reporting of air pollutants (EEA, 2013) includes only 4
PAHs (benzo[b]fluoranthene (BbF), benzo[k]fluoranthene
*Corresponding author.
Tel.: +420 597324905
E-mail address: lenka.kubonova@vsb.cz
(BkF), benzo[a]pyrene (BaP) and indeno[1,2,3-cd]pyrene
(INP)), as mentioned in Table S1. These PAHs are mainly
bound to particulate matter. Organic matter can be condensed
to form particles either via nucleation-condensation or via
condensation on existing particles. As a result, organic
matter is present as different particle types with various
morphologies (Holoubek, 1996; Ravindra et al., 2008;
Lisouza et al., 2013; Torvela et al., 2014; Mikuška et al.,
2015; Tiwari et al., 2015).
The sampling of particulate matter (PM) from combustion
in residential stationary sources is still challenging. The
problems of PM formation include the unstable combustion
process, especially in manually fed heating appliances due
to changeable fuel uptake, the unstable temperature, the
amount of flue gases and the changeable combustion rate.
It is appropriate to use a dilution tunnel to achieve isokinetic
conditions for sampling. Three methods that address the
measurement of PM10 and PM2.5 in stacks using impactors,
virtual impactors and cyclones have been standardized
(Bergmans et al., 2014). Impactors, such as the electrical
low-pressure impactor (ELPI), the Dekati Low-Pressure
Impactor (DLPI), and the Dekati Gravimetric Impactor (DGI)
are suitable devices for measuring fine particles (Dekati,
2017). Cascade impactors are air sampling devices that
comprise a series of stages whose flow characteristics
separate particles into finer fractions (Galarneau et al.,
2017). There are several studies that have used DLPI and

Horák et al., Aerosol and Air Quality Research, 18: 849–855, 2018
850
discussed the PAHs emission from the combustion in
boilers such as from a pellet boiler with a nominal output
of 25 kW, which included 30 PAHs (Lamberg et al.,
2011), from different types of boilers considering a sum of
27 PAHs (Johansson et al., 2004), or from biomass boilers
with higher nominal outputs (40–50 kW) (Leskinen et al.,
2014; Torvela et al., 2014). The PM and PAH emissions
from other residential heating facilities, such as stoves and
masonry heaters, that used DLPI have been studied, e.g. by
Boman and Lamberg (Boman et al., 2005; Lamberg et al.,
2011).
The aim of this study was to study the particle phase and
gas phase emissions of 4 PAHs from domestic heating
boilers of old and modern construction commonly used in
Central and Eastern Europe via combustion of different
types of fuels. The results of the sampling of particulate
matter and consequent PAH analysis obtained by the
Dekati Low-Pressure Impactor (DLPI) (Dekati, 2017) were
compared with a cyclone that was used simultaneously. To
our knowledge, there has been no comparative study of the
cyclone and DLPI impactor that focused on PAH emissions
from domestic hot water boilers.
MATERIAL AND METHODS
The boilers, fuels, test set-up, conditions and the emission
measurements are presented briefly in this section and
were described in detail in our previous work (Krpec et al.,
2016; Horak et al., 2017). Only 11 of those 25 combustion
tests are included in this study. This is due to the time
coverage of the DLPI, which was higher than 50% of the
time coverage of the cyclone.
Boilers and Fuels
The tested combustion devices (Fig. S1) represent the
most frequently used boiler designs for domestic heating in
the countries of Central and Eastern Europe. They are
described in detail in our previous publications (Krpec et
al., 2016; Horak et al., 2017), and the designation of the
boilers has been retained as described in our previous
publications.
The combustion tests were performed with four different
fuels: lignite (L1, L2), wood pellets (WP), wet spruce wood
logs (WW) and mixed fuel (MF). The mixed fuel was a
mixture of lignite (44%), wet spruce logs (34%) and wood
chips (9%) placed into polyethylene terephthalate bottles.
The wood chips were soaked with used vegetable frying
oil (13%) (Krpec et al., 2016). The elementary compositions
and calorific values of the fuels were determined prior
to the combustion of each fuel (Table S2).
Test Set-up and Emission Measurements
All tests were conducted in an accredited testing
laboratory at the Energy Research Center (VŠB-TU Ostrava).
The boilers were operated either at nominal output (Pnom)
or at reduced output (30% of nominal output, Pmin)
according to their operating manuals and according to the
requirements of the EN 303-5:2012 standard. A dilution
tunnel was operated by considering the AS/NZS-4013:2014
standard and the EPA Method 5G.
The DLPI (Dekati, Fig. S2) was used to determine the
PM concentration and mass-size distribution in the dilution
tunnel via isokinetic sampling in the middle of the flue gas
stream. The sampling was made with regards to the EN
13284-1 (BSI, 2001), ISO 11338-1 (ISO, 2003) and EN
ISO 23210 (ISO, 2009) standards, which do not include
the sampling of the PM1 and PM0.1 fractions (Drastichová,
2015). The flue gas was cooled down in the dilution tunnel
ahead of the DLPI. The DLPI was heated during collection
to a temperature of 80°C to prevent condensation of flue
gases and to be closer to the temperature of flue gases in
the dilution tunnel. Any diluter was applied ahead of the
DLPI. The DLPI enables the sorting of the PM into thirteen
different sized fractions with diameters of approximately
0.03 µm to 10 µm. The sums of the particle masses on the
individual collection substrates provide the distribution of the
PM fractions: PM0.1 (0–2 stage), PM1 (0–7 stage), PM2.5
(0–9 stage) and PM10 (0–13 stage), Table S3. Behind the
DLPI was a polyurethane foam (PUF) for the collection of
PAHs in the gaseous phase. The use of PUF is meaningful
because, for example, for benzo[a]pyrene, the vapor fraction
can represent a significant amount of its total concentration.
PUF is an efficient sorbent due to its relatively high capacity,
low cost and low impedance (Paolini et al., 2016). The
correctness of the results from the DLPI was compared in
this study with the results from a cyclone (Tecora) that was
simultaneously used in parallel to determine the PM
concentration and mass-size distribution. The time coverage
of the DLPI in comparison with the time coverage of the
cyclone is summarized in Table S4. The results of the EF
(emission factor) PAHs from the cyclone are presented in
detail in our previous work (Horak et al., 2017).
PAH Analysis
The PAH analysis was performed in the laboratory in
the Nanotechnology Centre (VŠB-TU of Ostrava). The
purification of PUF before analysis was performed in a
Soxhlet extraction apparatus. The quantification of the
PAHs was performed via gas chromatography in connection
with a mass spectrometer (GC/MS) Trace GC Ultra/TSQ
Quantum XLS from Thermo Scientific in simple ion
monitoring (SIM) mode. The system was calibrated with a
diluted standard solution of PAHs (Absolute Standard,
Inc., Part 10017, 2000 µg mL–1 in dichloromethane). The
blank samples were analyzed together with the samples,
and no detectable PAHs were identified in those blanks (in
the purified PUFs, aluminum foils, in the solvents or in the
extractor vessels). The aluminum foils were analyzed in
groups from different DLPI runs from the same combustion
tests. The limits of detection were determined to be in the
range of < 0.15 to < 1.0 mgPAH/kgfuel. The uncertainty of the
PAH analysis was determined to be 23%. The uncertainty
of sampling during the combustion tests was defined as 20%;
thus, the total uncertainty of the measurement was 30%.
Emission factors (EFs) of the PAHs were used to calculate
the participation of individual PAHs in the total PAH
emissions.

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RESULTS AND DISCUSSION
The EFs of the 4 PAHs as defined by UNECE
nomenclature for reporting of air pollutants (EEA, 2013)
were discussed in detail. First, the distribution of the 4 PAHs
in the PM fractions and PUF was discussed. Furthermore,
the overall EFs Σ 4 PAHs from 11 combustion tests were
summarized.
Comparison of PAH Emissions from the DLPI and the
Cyclone
A comparison of the EF PM from the cyclone and the
DLPI was described in our previous study (Krpec et al.,
2016). The DLPI enabled sorting of PM fractions into
PM0.1, PM1, PM2.5 and PM10, whereas the cyclone enabled
sorting of PM into PM2.5 and PM10. Particle size is perhaps
the most important property that determines particles
behavior in a gas (Kantová et al., 2017). The distribution
of the 4 PAHs in the particular PM fractions captured by
the DLPI is shown in Fig. 1. They can be separated into 4
groups: a) PAHs in PM0.1, b) PAHs in PM0.1-1, c) PAHs in
PM1-2.5, and d) PAHs in PM2.5-10 (Table S4). Only the time
coverage via DLPI sampling that was higher than 50% of
the time coverage via cyclone was considered for further
discussion (Table S4). Finally, only 11 of the 25 combustion
tests were included in this study, and the designation of
combustion tests remained as reported in Horak (Horak et
al., 2017).
It was reported in the literature (Sahu et al., 2008;
Lisouza et al., 2013) that PAHs with a higher molecular
weight (MW > 228 g mol–1) preferentially segregate into
fine particles. The DLPI data showed that 4 PAHs with
MW > 228 g mol–1 were primarily detected (more than
50%) on PM1 except for tests no. 4, 20, 24 and 25, in
which the 4 PAHs were mainly (more than 50%) detected
in the gas phase (PUF), and for test no. 3, in which the 4
PAHs were also detected on larger PM and in PUF (Fig. 1,
Table S4). The cyclone data showed that 4 PAHs were
mostly detected on PM2.5, except for test no. 18 in which the
4 PAHs were mainly detected in PUF (Fig. 2, Table S5).
Because in several tests the distribution of the 4 PAHs
was comparable or higher in polyurethane foam (PUF) than
in the PM of DLPI and its distribution was not negligible
(Figs. 1 and 2), the 4 PAHs were further considered as the
sum in PM10 + PUF.
The effectiveness of the DLPI capture (EFs Σ 4 PAHs in
PM10) was mainly lower than or comparable with the
cyclone capture (EFs Σ4 PAHs in PM10), except for the
tests no. 1 and 18 (Figs. 3 and 4).
The reasons for the lower DLPI effectiveness are as
follows:
i) Any diluter was applied ahead of the DLPI; thus, it was
impossible to cover the entire combustion period using
one DLPI (column DLPI coverage, Table S4). The two
available impactors were used sequentially during the
combustion tests with a time delay due to their cleaning,
reassembly and pre-heating. The average values measured
in the adjacent collections were used to calculate the
EFs. The number of used DLPIs is mentioned in Table
S4. It is recommended to increase the dilution ratio to
cover the entire period of sampling by the DLPI to avoid
filling the DLPI or use a diluter ahead of the DLPI.
Fig. 1. Distribution of the 4 PAHs in the particulate matter of DLPI and in PUF.

Horák et al., Aerosol and Air Quality Research,
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Fig. 2. Distribution of the 4 PAHs in the particulate matter of cyclone and in PUF.
Fig. 3. Dependency graph of EF Σ 4 PAHs in PM10 of the cyclone on the EF Σ 4 PAHs in PM10 of the DLPI.
ii) A decrease of pressure below the 8th stage in the DLPI
(< 0.4 bar) could cause desorption of PAHs, especially
from the PM1 fraction, and hence lower the EF Σ 4
PAHs in PM10 that were measured via the DLPI (Hays
et al., 2003). A solution could be the use of less stages
in the DLPI so the pressure would not be that low and
the pressure would be comparable with the pressure in
the dilution tunnel.
The effectiveness of the DLPI and cyclone should be
compared by including the rinsing of the DLPI, especially
in the case of lighter PAHs; however, the DLPI was rinsed
only in tests no. 3 and 4 (not included in Fig. 4).

Horák et al., Aerosol and Air Quality Research,
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Fig. 4. Comparison of the EF Σ 4 PAHs in the DLPI vs. the cyclone.
The highest EFs of 4 PAHs were observed in the old-
type boiler (B3) by comparison of the same fuel and the
same conditions of combustion, see Table S4 and Fig. 4. It
was confirmed that the efficient combustion at Pnom generated
lower emissions of 4 PAHs and PM (for all fractions) as
compared for B1, B4 and B5 boilers which was reported as
well in other studies (Kubica, 2007; Ravindra, 2008).
CONCLUSIONS
One old-designed and three modern domestic heating
boilers were tested, and their emissions of particulate
matter (PM) and polycyclic aromatic hydrocarbons (PAHs)
were compared. A Dekati Low-Pressure Impactor (DLPI,
Dekati) sorting of the PM fractions into PM0.1, PM1, PM2.5
and PM10 was used to determine the EFs of the 4 PAHs in
the dilution tunnel via isokinetic sampling, which was
compared with a cyclone. The 4 PAHs were mostly detected
in the fine particles of PM1 in the DLPI, whereas they were
detected on the fine particles of PM2.5 in the cyclone, and in
some cases, they were mainly detected in the PUF used for
the collection of the gas phase. The effectiveness of DLPI
sampling was generally comparable or lower than the
cyclone sampling. This is because one DLPI could not
cover the entire duration of combustion tests and had to be
replaced several times and PAHs could desorb especially
from the PM1 fraction due to the low pressure in the DLPI.
Sampling by the DLPI can possibly be improved by
increasing the dilution ratio in the dilution tunnel to cover
the entire period of sampling by the DLPI or by using a
diluter ahead of the DLPI.
SUPPLEMENTARY MATERIAL
The results described in the main text of the article are
presented in graphs and tables in the Supplementary Material.
The schematic diagrams of the tested combustion devices
are shown in Fig. S1. The photo of the Dekati Low-Pressure
Impactor (DLPI, Dekati) is presented in Fig. S2.
The characteristics of the 4 PAHs are summarized in
Table S1. The extensive experimental data are shown in
Tables S2 (the specifications of used fuels), S3 (the summary
of particulate matter), S4 (EF Σ 4 PAHs in the DLPI
fractions) and S5 (EF Σ 4 PAHs in the cyclone fractions).
Supplementary data associated with this article can be
found in the online version at http://www.aaqr.org.
ACKNOWLEDGEMENTS
The presented work was financially supported by the
European regional development fund (project “Increase of
research capacity and quality of INEF center“, identification
code CZ.1.05/2.1.00/19.0407) RDI OP, with the financial
support from European Regional Development Fund, by
the project SP2017/105 “Characterization of ashes and dust
emissions from combustion of solid fuels in households”

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854
and by the project LO1404 “Sustainable development of
ENET Centre”.
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Received for review, October 24, 2017
Revised, February 1, 2018
Accepted, February 24, 2018